In recent years, many attempts have been made to provide computers different from a von Neumann computer and to provide artificial intelligence systems, by using artificial neural networks that are analogous to the neural network of living things. The neural network of living things is constituted of neurons and synapses connecting the neurons. The neuron includes a nerve cell, neurite, dendrite and the like. The excited state of any neuron is transmitted through a synapse to an adjacent neuron or an effector such as the muscle.
An artificial neural network analogous to the neural network is disclosed in Japanese Patent Laid Open No. H5-89268. This artificial neural network comprises a neuron circuit and a plurality of synapse circuits connected to the neuron circuit. The neuron circuit generates pulses when it is excited. In the network disclosed in Japanese Patent Laid Open No. H5-89268, the resistance of the resistor provided in each synapse circuit is changed, thereby varying the current-driven capability. Thus, the neuron circuit and such synapse circuits connected to the neuron circuit constitute the artificial neural network. When the current supplied to the neuron circuit exceeds a predetermined value, the neuron circuit is activated, and generates pulses that indicate that the neuron circuit is excited.
The artificial neural network disclosed in Japanese Patent Laid Open No. H5-89268 is activated (or excited) only when the input to the neuron circuit from the synapse circuits exceeds the predetermined value. That is, it acts quite differently from the real neural network. That is, in the real neural network, each neuron assumes an excitable state or a non-excitable state, depending on a history of input from the synapses. In the artificial neural network disclosed in Japanese Patent Laid Open No. H5-89268, however, the neuron circuit cannot act corresponding to such an input history.
Other techniques concerning artificial neural networks are disclosed in Japanese Patent Laid Open Nos. H6-266867, H6-290286, H7-168901, 2003-108914, and 2003-223790.